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Understanding tie strength in social networks using a local “bow tie” framework

Understanding factors associated with tie strength in social networks is essential in a wide variety of settings. With the internet and cellular phones providing additional avenues of communication, measuring and inferring tie strength has become much more complex. We introduce the social bow tie fr...

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Autores principales: Mattie, Heather, Engø-Monsen, Kenth, Ling, Rich, Onnela, Jukka-Pekka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6008360/
https://www.ncbi.nlm.nih.gov/pubmed/29921970
http://dx.doi.org/10.1038/s41598-018-27290-8
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author Mattie, Heather
Engø-Monsen, Kenth
Ling, Rich
Onnela, Jukka-Pekka
author_facet Mattie, Heather
Engø-Monsen, Kenth
Ling, Rich
Onnela, Jukka-Pekka
author_sort Mattie, Heather
collection PubMed
description Understanding factors associated with tie strength in social networks is essential in a wide variety of settings. With the internet and cellular phones providing additional avenues of communication, measuring and inferring tie strength has become much more complex. We introduce the social bow tie framework, which consists of a focal tie and all actors connected to either or both of the two focal nodes on either side of the focal tie. We also define several intuitive and interpretable metrics that quantify properties of the bow tie which enable us to investigate associations between the strength of the “central” tie and properties of the bow tie. We combine the bow tie framework with machine learning to investigate what aspects of the bow tie are most predictive of tie strength in two very different types of social networks, a collection of medium-sized social networks from 75 rural villages in India and a nationwide call network of European mobile phone users. Our results show that tie strength depends not only on the properties of shared friends, but also on non-shared friends, those observable to only one person in the tie, hence introducing a fundamental asymmetry to social interaction.
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spelling pubmed-60083602018-06-26 Understanding tie strength in social networks using a local “bow tie” framework Mattie, Heather Engø-Monsen, Kenth Ling, Rich Onnela, Jukka-Pekka Sci Rep Article Understanding factors associated with tie strength in social networks is essential in a wide variety of settings. With the internet and cellular phones providing additional avenues of communication, measuring and inferring tie strength has become much more complex. We introduce the social bow tie framework, which consists of a focal tie and all actors connected to either or both of the two focal nodes on either side of the focal tie. We also define several intuitive and interpretable metrics that quantify properties of the bow tie which enable us to investigate associations between the strength of the “central” tie and properties of the bow tie. We combine the bow tie framework with machine learning to investigate what aspects of the bow tie are most predictive of tie strength in two very different types of social networks, a collection of medium-sized social networks from 75 rural villages in India and a nationwide call network of European mobile phone users. Our results show that tie strength depends not only on the properties of shared friends, but also on non-shared friends, those observable to only one person in the tie, hence introducing a fundamental asymmetry to social interaction. Nature Publishing Group UK 2018-06-19 /pmc/articles/PMC6008360/ /pubmed/29921970 http://dx.doi.org/10.1038/s41598-018-27290-8 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Mattie, Heather
Engø-Monsen, Kenth
Ling, Rich
Onnela, Jukka-Pekka
Understanding tie strength in social networks using a local “bow tie” framework
title Understanding tie strength in social networks using a local “bow tie” framework
title_full Understanding tie strength in social networks using a local “bow tie” framework
title_fullStr Understanding tie strength in social networks using a local “bow tie” framework
title_full_unstemmed Understanding tie strength in social networks using a local “bow tie” framework
title_short Understanding tie strength in social networks using a local “bow tie” framework
title_sort understanding tie strength in social networks using a local “bow tie” framework
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6008360/
https://www.ncbi.nlm.nih.gov/pubmed/29921970
http://dx.doi.org/10.1038/s41598-018-27290-8
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